{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['survived', 'pclass', 'sex', 'age', 'sibsp', 'parch', 'fare',\n",
       "       'embarked', 'class', 'who', 'adult_male', 'deck', 'embark_town',\n",
       "       'alive', 'alone'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "titanic=sns.load_dataset('titanic')\n",
    "titanic.columns\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "基本代码："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xc22e5c0>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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CVR0CVgNbgXuBm6tqZ5J1SZYDJPmFJKPAa4EPJNnZVT2SpKl1+e0jqmoLsGVc29q+5W30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\nUJAktf4/f4mp9sZo65IAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x56aaf60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='class',y='survived',data=titanic)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "\n",
    "<font color=#0099ff size=5 face=\"黑体\"> 01 直方图</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xc668a20>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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mpxBu3UVjVkSol5sWZfGzN4r5/YZDfOXcqXhttlpziuxK5XFmU0k1FfWtXH56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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc649fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#去除'age'中的缺失值，distplot不能处理缺失数据\n",
    "age1=titanic['age'].dropna()\n",
    "sns.distplot(age1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在上图中，矩形表示在不同年龄段的数量分布，并且 distplot() 默认拟合出了密度曲线，可以看出分布的变化规律。\n",
    "'kde' 是控制密度估计曲线的参数，默认为 True，不设置会默认显示，如果我们将其设为 False，则不显示密度曲线。\n",
    "'bins'是控制分布矩形数量的参数，通常我们可以增加其数量，来看到更为丰富的信息。\n",
    "'reg' 参数用于控制直方图中的边际毛毯，通过控制'reg'是实现毛毯是否显示。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xcea0160>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LVkx03SVF+Ay8cUwrO6EUTELYBSwTkSUi4gI2AVsn7LMVuNN6/AngZXORjmsR\ncYpIofU4GfgIcGCmhY82HQNuCqOkWR1w3SVF/OF4J6MenY8w3rp16zh69CgNDQ243W4ef/xxgJ4J\nu2lcA4OjHobHvFEV22vLc8lKcfKaVnZCatqEYPWd3gO8CBwCnjDGHBSR+0XkFmu3R4ACEakHvgKc\nHZoqIo3Ad4E/FpFmEVkBpAAvisg+YA/QAvwgdF/LHtGwbMVE1y4rZGTMx26dyHMep9PJli1b2LBh\nA8uXL+f2228HGNG4vtC54dTRE9vOJAfvqSzg1SMdOmgihIKamGaMeQF4YcK2b4x7PALcNsV7F09x\n2CuDK2Ls6BgYpao4y+5inOePKgpIThJePdLONZWFdhcnqtTU1FBTU3P2+de+9jWN60m0n52lHD3X\nEMDf+n3xYBvH2gepnJdpd3Higs5UZvLZkJ+6auGMj9Mx4OaaKKpFgf+GOdWL8vndkXa+WrPc7uKo\nCAtFbAeWrbB7HaOJrlvmv/by6pF2TQghomsZhYjb46N3eCyqmtUB115SyLut/ZzpS5hh8yqEorHL\nCPyDJpYUZuh1hBDShBAiXYP+kybamtUA77vEX5N65bCeOGrmOqJsOPV477ukiDePdzLk9thdlLig\nCSFEOgaia5byeCtKsinPT+O5/aftLoqKQR0Do+SkJeNyRt+fiw+tnM/ImI+X3z1jd1HiQvT9D8eo\n9ihOCCLChy9bwBv1HWdbMkoFKxruAjiVq5YUUJSVwnN7tbITCpoQQsSu5YGD9ZHVJXh9hu0HWu0u\niooxHf1u2++DMJUkh1CzqpjfHj7DwKh2G82VJoQQOWMlhPnZExfMjA4rF2SzpDCD5/dPnGSu1MW1\n9Y9QHKVxDfCRNQsY9fj4zaE2u4sS8zQhhEhb3wg5acmkJkfHshUTiQgfWV3Cm8c6dR15FTRjDG19\nI8zPjs4WAvjvs1ycncqz2m00Z5oQQqS1N7pPGoAPry7BZ2DbAT1xVHD6RjyMjPmituUL4HAINZeV\n8OqRdnqHdbG7udCEECJt/aNRfdIAVM3P4tLiLP5rd7PdRVExos2auxLtsX3r5aW4vT627mmxuygx\nTRNCiLT1jkT9SSMi3LF+IftbejnQ0mt3cVQMiJWEsKo0m5ULsnmstknXNpoDXboiBLw+Q/vAaNRd\neJts2QKP1+B0CPc/V8fH1p67z9FslupQ8a+tz3+9KZpie7K4BlhalMnWvaf4/188TFme/57iGtcz\noy2EEOgcGMXrM1F/DQEgzZXEZaU57G3qwe3x2V0cFeUCLYR5MRDba8tzSU4SdjXqndRmSxNCCARq\nUfOiqBZ1MesW5zPq8bG/ZeLAHMQ8AAAeLElEQVTy/0qdL9pHz42XmpzE6tJc9jb3Mjqm9/+YDU0I\nIRCoRUVTs/piFhWkU5SVovekVdNq64vuOQgTrVuSj9vjY2+zXiObDU0IIdAaIxfeAkSE9Yvzaeoe\n5lTPsN3FUVGstW80JrqLAsrz0ijOTqW2oVMvLs+CJoQQON07TJJDonbZislcsTAPp0O0laAu6nTP\nMCU5sVHRAauysySfU70jNHdrZWemNCGEQEv3MMXZqTiTYufXmeZKYnVZLnuae7S/VU1q1OPlTP8o\npbnpdhdlRtaW5+JKcmhlZxZi5y9YFGvpGaY0L83uYszYVVZ/655mvbisLnSqx98VGmuxnZqcxNry\nXPa19NA7pDOXZ0LnIYTAkbYBKgozphwfHa3K8tJYkJNKbUMXxhhExO4iqSjSYnW5vNvaF3OxvX5J\nPrWNXTz1TjOfu2aJ3cWJGdpCmKMxr4++4TFy02Pn+kGAv7+1gNO9I7zTpK0Edb6WniEA8tJiL7YX\n5KZRnpfGf+48qReXZyCohCAiN4nIYRGpF5H7Jnk9RUR+Yb2+U0QWW9sLROS3IjIgIlsmvOdKEdlv\nvef7EqPV09beEQyQl55sd1FmZU1ZDilOB//5h9iqAYbK9u3bqaqqorKyEqB44uuJHNvN3cMIkJ0W\nm7G9fkkB9WcG9FrCDEybEEQkCXgIuBlYAdwhIism7HYX0G2MqQS+B3zH2j4CfB34n5Mc+t+Au4Fl\n1s9Ns/kCdguMZIjFFgJAitXf+ty+Uwm3UqTX62Xz5s1s27aNuro6gHyN7XNauofJTksmyRGT+YzL\nSnPITnXy89rErOzMRjAthPVAvTHmuDHGDTwObJywz0bgUevxk8ANIiLGmEFjzOv4T56zRKQEyDbG\nvGn87bmfAh+byxexS0tPICHEZi0K4MpFeYx6fGxLsHsu19bWUllZSUVFBS6XC6ALje2zmnuGYzqu\nXU4HH12zgO0HW/VuakEK5qJyKdA07nkzcNVU+xhjPCLSCxQAHRc55vg1mJutbTGnudvfz5oTo81q\ngNLcNIoyU/j33x3DN667Nd4XBmtpaaG8vHz8JjcXxmHCxnZL9zBFWbEzKW0yWSlORsZ8/H/PHOTK\nRXlnt8d7bM9WMC2EydqLE6/SBLPPrPYXkbtFZLeI7G5vb7/IIe1xonOInLRkkmNoDsJEIsLlC3Np\n7Byia9Btd3EiZoqLjRGJ7WiP65ExL6d6h8nPiM2u0IDy/HQKMly809Rtd1FiQjB/xZqB8dWoMmDi\njXnP7iMiTiAHf/P7Yscsm+aYABhjHjbGVBtjqouKioIobmQdbx+IqRnKU1lbnosAexLoxCkrK6Op\naXzjFxcRiu1oj+sTnUMYA4WZsd1CCFR2GtoH6RlKnMrObAWTEHYBy0RkiYi4gE3A1gn7bAXutB5/\nAnjZXGSslzHmNNAvIn9kjcD4LPDMjEtvM2MMx9oHY75ZDf6L4kuKMnjnZE/CDNNbt24dR48epaGh\nAbfbDZCPxjbgr+gAcRHba8vzMMAeHVo9rWkTgjHGA9wDvAgcAp4wxhwUkftF5BZrt0eAAhGpB74C\nnB2aKiKNwHeBPxaR5nGjOL4I/BCoB44B20LzlSKnvX+UgVFPzNeiAi4vz6Nz0E1T15DdRYkIp9PJ\nli1b2LBhA8uXLwfo0tj2O94xCBAXrd/8DBeLC9ITqrIzW0HNVDbGvAC8MGHbN8Y9HgFum+K9i6fY\nvhtYFWxBo9Gxdv9JUxQnCWHlgmye2SPsbe5lYUGG3cWJiJqaGmpqagAQkVbQ2AY41j5AcXYqKc7o\nvw9CMNaU5/LMnlOc7h1hQW5sLcURSbF7JTQKHO/wN6sL46BZDf41YC4tzmJfSy9en9akEtmx9kEq\niuKnUnDZghwcAnt13a6L0oQwB8fODJKa7IjpIacTrSnPZXDUczbZqcRjjOF4+0BcJYT0FCeXzM9i\nX3MvPu02mpImhDk4dLqPZfOycMTmygSTumR+FqnJDvY26R2nElVLzzD9Ix6q5mfZXZSQWlOWS+/w\nGCc6E+Ma2WxoQpgln89woKWX1WU5dhclpJKTHKwsyeHgqV5G9D4JCWmfdfvJ1WW5NpcktJaXZJOc\nJNptdBGaEGbpeMcg/aMe1sTZSQP+bqNRj4/fvnvG7qIoG+xt7iE5Sbi0JL5aCC6ng+Ul2exv7sXt\n8dldnKikCWGW9lm1jNXl8dVCAKgoyiAzxckzeyadK6ji3L6mXpaXZMfNCKPx1pblMjzm5fX66Jsd\nHg00IczSvuZe0pKTqCzKtLsoIecQYXVZDi8fPkPfSGKtgJro4rUrNKByfiZpyUla2ZmCJoRZ2tnQ\nxeqynJi6j/JMrCnLxe3x8eKBVruLoiKo7nQf/aMeLi/Pm37nGOR0OLisNIcddW0MuXUF1Ini869Z\nmDV1DXHodB83LJ9nd1HCpiwvjUUF6WzdqzWpRLKjrg2HwPurom99pVBZXZ7DkNvLS4f0GtlEmhAm\nONE5yH/84QSf/VEtL7/bNuk+Lx3yb79xxQU32IobIsItaxbwRn0HZ/pHpn+Dimo+Y/jd4TP88PXj\nfPWp/WeXbZ9oR10bVy7KoyBOZt9PZnFBBsXZqWzd02J3UaKOJoRxGjoG+dEbDTR1D3HszAB/8pPd\nPPB8Hb4Js3a37W+lcl4mSwrjZ+LOZDauXYDPwPP7EuvGOfHouX2neLGujWG3l1++3cyHv/86O493\nnrdPQ8cgdaf7uHHFfJtKGRkOEW5Zu4BXDrfTnUDLvQdDE4LF6zM8/U4z2anJfOkDy3jlf72fO69e\nxA9ea+BLP3/n7Jj81462U9vYxaZ15dMcMfZVzstiRUm2XoCLcQ0dg/zheBfXLC3gnusreel/vI/C\nTBefeaT2vC7B7+44Qmqyg41rY/J+PjNyy5oFeHyGbXqN7DyaECx7mnroGHBz06piMlOcJCc5+OYt\nK/mbmuU8v/80//2HO9l+oJWv/+oAZXlpfObqRXYXOSI2rl3AnqYeTnQO2l0UNQvGGHbUtZGV6uTG\nFcWICAsL0vnlF9/D2vJc/uLn7/DdXx/mh68d59m9p/izayuYn51qd7HDbuWCbJYWZfCMdhudRxOC\n5ffHOijJSWVFSfbZbSLCn11XwUOfuoL9Lb184T/eYmDUyz/etiYux2hP5iNrFgBoKyFGne4dobFz\nkOuWFeFynjvdc9Nd/PSu9Xx0zQK+/3I9337+ENcuK+QL71tqY2kjx3+NrJTaxi5OWfdFV0Eufx3v\n2vpGON07wkdWlyCTrEv04dUlvGdpAYda+1hZkkNODN94fKZKc9O4prKAx2tP8ufvXxq3w2zj1d6m\nHpJEuLz8whn1qclJfH/TWu69oZLuoTGqF+VNGv/x6r9dUco//eYIP689yV9+qMru4kQFPbvxzzoW\n4LLSqSfj5GW4eM/SwoRKBgF3Xr2YU70j7KibfNSVik4+n2Fvcw/L5meSnjJ53U9EqJyXxbrF+QmV\nDMB/v+UbLp3PYztP6rpdFk0IwIGWPiqKMshKTbw/9sG4Yfl8yvLS+PHvG+0uipqBd5p66BvxxN0i\ndaH0uWsW0zno5jkdSQdoQqC5e4j2gVEuLc6efucEleQQ7rx6MbUNXRw8pctix4pXj7QjwCXz4295\nlVB5z9ICls3L5MdvNOjtNdGEwGtHOwConKcnzcXcXl1OWnISP3mj0e6iqCC9erSd0rw00l16qXAq\nIsIfX7OYg6f62H2i2+7i2E4TwtF2ctKSmRcnt8EMl5z0ZG6vLuOpd1po6NAhqNGud2iMvU09LJsX\nX0tYh8Otl5dSkOHiu78+kvCthIROCD6f4ffHOqksyky4C2qzsfkDlbiSHPzDrw/bXRQ1jT80dOIz\n2vINRrrLyZc+UMmbxzt51eoxSFRBtSVF5Cbgn4Ek4IfGmAcnvJ4C/BS4EugEPmmMabRe+ypwF+AF\n/sIY86K1vRHot7Z7jDHVIfg+M3KsfYCeoTEWx/kSFLP12M6TF2z702uX8C8v1/OF63q5LA6WSN6+\nfTv33nsvXq8X4ILFqWI1tnc3duFyOijPS4v0R8eEibHtcAjl+Wl8Z9u7XFtZiMORmBXEaVsIIpIE\nPATcDKwA7hCRFRN2uwvoNsZUAt8DvmO9dwWwCVgJ3AT8q3W8gOuNMWvtOGGAs32GiwrS7fj4mHT3\ndRXkpSfz4PZDMd+89nq9bN68mW3btlFXVweQH0+xvbo0fpdnDzWnw8Ff3lhF3ek+nt2XuJMwg2kh\nrAfqjTHHAUTkcWAjUDdun43AN63HTwJbxN8HsxF43BgzCjSISL11vDdDU/y52dXYRWGmi4IMV9Dv\nmazWnEiyUpO594ZlfPPZOrbuPRXT697U1tZSWVlJRUVFYFMXcRDbI2NeDrT0ctd7K6bf2ZLocQ3+\n9Y1++Ppxvv38Id5/ybyEnHMUTPWhFGga97zZ2jbpPsYYD9ALFEzzXgP8WkTeEpG7Z170uXvrRDdX\nJtjszFD4zNWLWVOey7eeraMrhleLbGlpobz8vEUK3cRBbO9t6mHMa6heFJ83uQkXh0N48L+tpmvQ\nzd+9cMju4tgimBbCZH8tJ/YVTLXPxd57jTHmlIjMA3aIyLvGmFcv+HD/CXU3wMKFC4MobnDO9I9w\nonOI/37V5IvUaY1pakkO4e8/vpqP/Mtr3P/sQf5p0+V2F2lWpujyikhshyuu4VxX6JWL8iZdzVNj\ne2qrSnP4s2sr+PffHeOWtQu4prLQ7iJFVDAthGZgfDWqDJjYyXZ2HxFxAjn4m99TvtcYE/j3DPA0\n/ub2BYwxDxtjqo0x1UVFobuL01uN/pOmerHWomajqjiLL76/kl/tOcVLMbqkRVlZGU1N4yv5uIhQ\nbIcrrsF/QblyXiZ5M+gKVed8+YPLWFKYwV/9ch8Do4l1m81gEsIuYJmILBERF/4LaVsn7LMVuNN6\n/AngZeOvfm0FNolIiogsAZYBtSKSISJZACKSAXwIODD3rxO83Se6SXE6WLkg9kfKRNJjO0+e/SnM\ndFGcncqXf7EnJm80sm7dOo4ePUpDQwNutxsgnxiPbZ/P8NaJbu0umoVAXD/1dgsfWjGflu7hhOs6\nmjYhWP2m9wAvAoeAJ4wxB0XkfhG5xdrtEaDAurD2FeA+670HgSfwX6TbDmw2xniB+cDrIrIXqAWe\nN8ZsD+1Xu7jdjV2sLc89b0lgNTNOh4PbqssYdnv5+jMRzech4XQ62bJlCxs2bGD58uUAXbEe20fP\nDNA34qF6cX6kPjIuLSrI4L3LCnls50l+d6Td7uJETFDzEIwxLwAvTNj2jXGPR4DbpnjvA8ADE7Yd\nB9bMtLChMuz2cvBUH59/X/CjMNTkSnLSuGH5PJ7bd5oNK0/xUev+CbGipqaGmpoaAESkFWI7tnef\n6ALQFkIIfHD5fFp7R/irJ/fx4pevS4hRRwlZPX6nqRuPz2gtKkSuXVbEmvJcvv7MAc70jdhdnIS2\nu7GbwswUnVsTAslJDr57+1raB0b55rMH7S5ORCRkQtjd2I2IfxSGmrskh/CPt61hyO3lW8/VTf8G\nFTa7GrtYv0SHUofKZWU5bL6+kqffaeGVw2fsLk7YJWRC2NXYxaXF2WTr/Q9Cprahi+uWFfH8vtN8\nc+tBHdpog9O9wzR3D1O9SFu+ofLYzpMUZrgozEzhK0/s5dHfN8Z1bCdcQvB4fbx9opt1Otw05K5b\nVkhhZgrP7GlhzOuzuzgJZ5c1lHqddoWGlDPJwca1C+gadPPbOG8lJFxCeLe1n0G3V68fhIEzycHH\n1i6ge2iM374b3ydONNrd2EWGK4nlJbrkdagtLcrk8vJcXjvSEdfXyRIuIexq9I/C0BZCeFQETpyj\nHRxt67e7OAllV2M3VyzK0wXtwuTmy0pwOR38as+pmF/YcSoJFzm7G7spzU2jJEeXBQ6XwInzN08f\nwOeLzxMn2vSNjPFua59ePwijzBQnN60qprFzkP96q9nu4oRFQiUEYwy7Gru0dRBmmSlObl5VTG1j\nF0/G6YkTbd4+0Y0x2vINtysX5bEoP53/88KhmF7YcSoJlRBOdg1xpn9Urx9EwBWL8li/OJ8HXjhE\nx8Co3cWJe7sau0hyCGsX5tpdlLjmEOFjl5fSP+Lhgefjb1mLhEoIb9R3AvBHFZoQws0hwgO3rmLI\n7eFvdW5C2L1R38nqshzSXUEtPqDmYH52Kp9/XwW/fLuZ1+PslpsJlRBePdLOgpxUlhbpfWYjYdn8\nLDZfX8kze07xzJ4Wu4sTt3qG3Oxr7uG6ZaFdNVVN7UsfWEZFYQZ/+V974qrrKGESgsfr441jHVy7\nrEhncUbQPddXcuWiPP7m6QOc6By0uzhx6Y36TnwGrrsksdbut1NqchLfv+NyugfH+N9P7o2bUUcJ\nkxD2NvfQP+Lhuku0FhVJziQH/7xpLSLwpZ+/w7Dba3eR4s6rR9rJSnWypkyvH0TSqtIc7rv5Ul46\ndIZHXm+wuzghkTAJ4cWDbSQnCe9NsDsgRYOyvHT+4bY17G/p5Yv/+RZuj85iDhWP18dLh9q47pIi\nnX9gg89ds5gNK+fzwAuHePqd2B9RlxBXoIwxvLD/NNdUFibEErbRaMPKYv7u1sv46lP7+fi//Z7b\nq8tJcpzruvvUVaG9jWSiqG3sonPQzYcvK5n09b9+ej9/d+tl/PXT+89uu9jzmewbzPPxZrLvTD8r\nlOUM5tiL73v+7PN3//YmPvfjXfzlE3vZ3djNygU5Z/dvfPDDZ/dbfN/z5z2faLrXIyEhqhT7W3pp\n7h6mZoqTRkXGHesXUrOqmP0tvfz49w0MJdjtCcPhhf2nSUtO4vqqeXYXJWGlJifxgzurKc1N47Gd\nJ3n9aOzeUCchWgi/fKsZV5KDD62Yb3dREspkq0K+d1kR6SlOfvVOCw+9Us8d6xdSlqdr98/GyJiX\n5/ad5gPL55HmSrK7OAkrEOd/8t4lPPlWMy8caLW5RLMX9y2EgVEPv3y7hQ+vLiE3XW86Hg2uWJjH\nn11bgc/Av//uGC8datPVUWfh2b2n6Bka49Pa3RYVUpxJ3LF+IR9cfq7i+eaxThtLNHNxnxCeeruZ\ngVEPn7l6kd1FUeOU56fzFx9YxpqyXF5+9wy3/usbHG7VxfCCZYzh0TcbqZyXydUVBXYXR1kcInzg\n0nPdd3f84A/c/2wdQ+7Y6B6N64QwOOrh+7+pp3pRHpeX65C8aJPmSuK26nI+tX4hp3pG+PD3X+OB\n5+sY0GsL03phfysHWvr4s2uX6LyaKPbZqxfxozcauPG7rwJE/XyFuE4I//JyPR0Do/z1h5frSRPF\nVpXm8NJX3scnrizjB6818MF//B3P7GnBqyulTmpg1MOD2w9RNT+LT1xZbndx1EXcv3EVT3z+arJS\n/Zdr/+Qnu6J6WfigEoKI3CQih0WkXkTum+T1FBH5hfX6ThFZPO61r1rbD4vIhmCPOVcvv9vGv//u\nGJ+sLueKhboCZLTLz3Dx4MdX89Sfv4eCTBf3Pr6H6//hFX78RkNYb0iyfft2qqqqqKysBCie+Hq0\nxbbPZ/irJ/fR0j3M/RtXnjd0V0Wn9UvyefZL7wX896y48XuvctdPdvHbw2cY9UTXRM1pRxmJSBLw\nEHAj0AzsEpGtxpjxK5bdBXQbYypFZBPwHeCTIrIC2ASsBBYAL4nIJdZ7pjvmrBhjeOrtFr761H5W\nlGTzrY0r53pIFUFXLMxj6z3vZUddK//31eN869k6vvVsHWvKc7liYS4rF+SwckE2FUUZpDjnNrLG\n6/WyefNmduzYQVlZGSkpKfkisiJaY7t3eIy/fno/z+8/zX03X8pVeu0gZiRbkwZf/d/X87M3T/Do\nm4385t0zZKY4uXppAasW5AD++2IXZ6fa1qMRzLDT9UC9MeY4gIg8DmwExgf4RuCb1uMngS3i/0Yb\ngceNMaNAg4jUW8cjiGMGxRhD+8AoR9sGOHS6j2f3nWZvUw/rF+fz8GevJDVZh+PFgsmGqN52ZTnX\nLivi0Ok+Drf28x9/OMGY19+NJAIl2aksKshgUUE6CwvSKctLpyDDRX6Gi7x0Fy6ng+QkITnJgdMh\n+Az4jDkbE7W1tVRWVlJRURH4yC6iKLbHvD5OdA5xtK2ft09288u3W+gecvPVmy/l7usqpj+Ast3E\nuN5+oJWirBTuvWEZx9sHqDvdxzsnu3mprg2Aq//Py6QmO1iYn87CfH9sLypIpzg7lXwrtrNSk8/F\ndZLgdDgY8/pwOmTOs9WDSQilQNO4583AVVPtY4zxiEgvUGBt/8OE95Zaj6c7ZlCOnhngQ9979ezz\nZfMyeeDWVWxat1Cb03GgODuV4uxUrq+ah88YOvpHWVKUwfH2QU52DXGic5CXDrXRMRDcipPvryri\nJ5/z/91uaWmhvPy8Png35+IzwLbY/vvt7/KD1/xr5Dgdwvur5vHlDy5jVWnObA6nokhykoOq4myq\nirMBGB3z8q3n6vjbjSs50TnEia4hTnYO8Xp9OyNjwQ3J/tdPXzHnybcy3VVvEbkN2GCM+VPr+WeA\n9caYL43b56C1T7P1/Bj+2tL9wJvGmP+wtj8CvID/2sVFjznu2HcDd1tPq4DDs/+6kyoEomFRcy3H\n+SJRjjwgGzhhPb8EeDQSsR2BuIbE+r8MRqKWY5ExJqhVPYNpITQD46tRZcCpKfZpFhEnkIO/+X2x\n9053TACMMQ8DDwdRzlkRkd3GmOpwHV/LEb3lEJGrgW8aYzZYz786yW5hie1wxzUk1v+lliM0gulw\n2gUsE5ElIuLCfyFt64R9tgJ3Wo8/Abxs/E2PrcAma6TGEmAZUBvkMZUKN41tpcaZtoVg9ZveA7wI\nJAE/MsYcFJH7gd3GmK3AI8DPrAtrXfhPAqz9nsB/Qc0DbDbGeAEmO2bov55SU9PYVup8015DiHci\ncrfVfNdyaDniSrT8DrUc0VmOySR8QlBKKeUX10tXKKWUCl5CJ4RwL59xkc8tF5HfisghETkoIvda\n278pIi0issf6qYlAWRpFZL/1ebutbfkiskNEjlr/hm3tDxGpGvd994hIn4h82Y7fRbzQuLY/rq3P\ni7nYTtguI/EvyXGEcUsMAHeEYomBID67BCgxxrwtIlnAW8DHgNuBAWPMP4S7DOPK0ghUG2M6xm37\ne6DLGPOg9QclzxjzVxEoSxLQgn8i1+eI8O8iHmhcny1LI1ES19Znx0RsJ3IL4eySHMYYNxBYYiDs\njDGnjTFvW4/7gUNcOEPWThuBR63Hj+I/qSPhBuCYMebEtHuqqWhcT82uuIYYie1ETgiTLckR8eAV\n/+qZlwM7rU33iMg+EflRuJu0FgP8WkTeEv/sWYD5xpjT4D/JgUjdsHcT8PNxzyP9u4gHGtd+0RTX\nECOxncgJYbKFjiLafyYimcAvgS8bY/qAfwOWAmuB08A/RqAY1xhjrgBuBjaLyHUR+MwLWJO4bgH+\ny9pkx+8iHmhc+0VFXENsxXYiJ4RgluQIGxFJxn/S/Kcx5ikAY0ybMcZrjPEBP+Dc6plhY4w5Zf17\nBnja+sw2qz840C98JtzlwH/ivm2MabPKE/HfRZzQuCaq4hpiKLYTOSHYtsSAiAj+GbCHjDHfHbd9\n/FKFtwIHwlyODOviHyKSAXzI+szxyzXcCTwTznJY7mBckzrSv4s4onEdXXENMRTbCTvKCMAa7vVP\nnFti4IEIfe57gdeA/UBgbdu/xh84a/E38RuBzwf6PMNUjgr8tSfwL2PymDHmAREpAJ4AFgIngduM\nMV1hLEc6/n7vCmNMr7XtZ0TwdxFPNK6jI66tssRUbCd0QlBKKXVOIncZKaWUGkcTglJKKUATglJK\nKYsmBKWUUoAmBKWUUhZNCEoppQBNCEoppSyaEGKYiPzKWrzrYGABLxG5S0SOiMgrIvIDEdlibS8S\nkV+KyC7r5xp7S6/U1DS27aET02KYiOQbY7pEJA3/kgUbgDeAK4B+4GVgrzHmHhF5DPhXY8zrIrIQ\neNEYs9y2wit1ERrb9nDaXQA1J38hIrdaj8uBzwC/C0zHF5H/Ai6xXv8gsMK/3AwA2SKSZa1br1S0\n0di2gSaEGCUi78d/IlxtjBkSkVeAw8BUNSOHte9wZEqo1OxobNtHryHErhyg2zphLgX+CEgH3ici\neSLiBD4+bv9fA/cEnojI2oiWVqngaWzbRBNC7NoOOEVkH/C3wB/w37P17/DfpeoloA7otfb/C6Da\nuktTHfCFyBdZqaBobNtELyrHGRHJNMYMWLWop/Evf/z0dO9TKtppbIefthDizzdFZA/+m240AL+y\nuTxKhYrGdphpC0EppRSgLQSllFIWTQhKKaUATQhKKaUsmhCUUkoBmhCUUkpZNCEopZQC4P8BYzZ9\nkc3R2oYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x733c5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#创建一个一行2列的画布,主要方便对比\n",
    "fig,axes=plt.subplots(1,2)\n",
    "\n",
    "#设置'reg'参数，加上观测数值的边际毛毯\n",
    "#需要用axes[]表示是第几张图，从0开始\n",
    "sns.distplot(age1,ax=axes[0]) #左图\n",
    "sns.distplot(age1,rug=True,ax=axes[1]) #右图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xd7cd2e8>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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odYw8zZ8PDQ1QVhb4zw4jmhB8zBjjWAshNiqS/MwETQjKPwK9jpGn+fOt7x99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\nKaVsmhCUUkoBmhCUUkrZNCEopZQC4P8D52G8NRnhDWwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcf1d1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#还可以通过更丰富的参数控制他们展示的细节，这些通过参数 'hist_kws' 、'kde_kws' 、'reg_kws' 来进行设置，\n",
    "#因为其中涉及到多个参数，参数间用逗号隔开，参数外面用大括号括住。\n",
    "fig,axes=plt.subplots(1,2) \n",
    "sns.distplot(age1,rug=True,ax=axes[0])\n",
    "sns.distplot(age1,rug=True,\n",
    "                     hist_kws={'color':'green','label':'hist'},\n",
    "                     kde_kws={'color':'red','label':'KDE'},\n",
    "                     ax=axes[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<font color=#0099ff size=5 face=\"黑体\"> 02 条形图</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xe047ac8>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ZBFwEjHf4fJKkJ6mzUKiqfcAaYCtwG3BNVW1Psj7J+QBJfi7JJPAa4INJtndVjyRpbl1+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\ny1CQJLUMBUlSy1CQJLUMBUlS6/8D74G3s3IGJVQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xca781d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='class',y='survived',data=titanic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "barplot() 利用矩阵条的高度反映数值变量的集中趋势，以及使用errorbar功能（差棒图）来估计变量之间的差值统计（置信区间）。需要提醒的是 barplot() 默认展示的是某种变量分布的平均值（可通过参数修改为 max、median 等）。\n",
    "我们可以通过设置'hue'参数，对x轴的数据进行细分，细分的条件就是'hue'的参数值，比如这里我们的x轴是'class'（仓位等级），我们将其按'sex'（性别）再进行细分。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xe968be0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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QmxYVfZ+F3nntaEk3J3de+3fgNXL3XDYzsxak0J7Cg8BvgW9HxMoM6zEzsxJqMBQktQbe\nj4hfN0I9ZmZWQg0OH0XEVqCTpHaNUI+ZmZVQwTfZAV6VNA1I5z2KiDsyqcrMzEqi0FBYmXy1Asqz\nK8fMzEqpoFCIiH/JuhAzMyu9QqfOngHUNSHewKJX1AxUVlZSXV1N165dGT9+fKnLMTMrmkKHj0bn\nLZcB3wVqil9O81BdXc2KFStKXYaZWdEVOnw0r9amVyX5dpxmZi1MocNHB+attgL6A10zqcjMzEqm\n0OGjeeSOKQjYAiwHfpRRTWZmViKFTp19LXB8RPQEppK7VuGvmVVlZmYlUWgo3BARX0g6DTgbmAzc\nk1lVZmZWEoWGwtbk+7nAvRHxLOBpL8zMWphCQ2GFpPuAi4DpkvbZheeamVkzUegv9ouAF4DBEbEW\nOBAY09CTJA2W9K6kpZKuq6fdBZJCUv8C6zEzswwUep3CX4Gn8tY/AT6p7znJlNt3kTsGUQXMkTQt\nIt6u1a4cGAnM3rXSzcys2LIcAjoZWBoRyyJiM/AoMLSOdrcA44FNGdZiZtboOpd9zTfb19C57OtS\nl1Kwgu/RvBu6AR/nrVcBp+Q3kHQC0CMinpOUP5WGmVmzN/q4taUuYZdl2VNQHdvSSfUktQL+Dbim\nwR1JwyXNlTR31apVRSzRzMzyZRkKVUCPvPXu5O7JsE05cCwwU9Jy4B+AaXUdbI6ISRHRPyL6d+nS\nJcOSzcz2blmGwhygl6Seya08hwHTtj0YEesionNEVEREBfAGMCQi5mZYk5mZ1SOzUIiIGmAEuVNZ\n3wEej4glksZJGpLV65qZ2e7L8kAzETEdmF5r2007aTsgy1rMzKxhvirZzMxSmfYUSq3fmCmZ7Ld8\n9XpaAx+tXl/013i6vKi7MzPbJe4pmJlZyqFgZmYph4KZmaUcCmZmlnIomJlZyqFgZmYph4KZmaUc\nCmZmlnIomJlZyqFgZmYph4KZmaUcCmZmlnIomJlZyqFgZmYph4KZmaUcCmZmlnIomJlZqkXfeS0r\nX7fbd7vvZmYthUNhN2zs9e1Sl2BmlgkPH5mZWcqhYGZmKYeCmZmlHApmZpZyKJiZWcqhYGZmKYeC\nmZmlHApmZpbyxWu2V6msrKS6upquXbsyfvz4Updj1uQ4FGyvUl1dzYoVK0pdhlmT5eEjMzNLORTM\nzCyVaShIGizpXUlLJV1Xx+P/LOltSQslvSzp0CzrMTOz+mUWCpJaA3cB5wDHABdLOqZWs7eA/hFx\nHPA7wEf+zMxKKMuewsnA0ohYFhGbgUeBofkNImJGRPw1WX0D6J5hPWZm1oAsQ6Eb8HHeelWybWd+\nBPyhrgckDZc0V9LcVatWFbFEMzPLl2UoqI5tUWdD6VKgP3B7XY9HxKSI6B8R/bt06VLEEs3MLF+W\n1ylUAT3y1rsDK2s3knQWMBY4PSK+yrAeMzNrQJY9hTlAL0k9JbUDhgHT8htIOgG4DxgSEZ9lWIuZ\nmRUgs1CIiBpgBPAC8A7weEQskTRO0pCk2e3AfsATkuZLmraT3ZmZWSPIdJqLiJgOTK+17aa85bOy\nfH0zM9s1nvvIzJoNT2iYPYeCmTUbntAwe577yMzMUu4pWJPVb8yUou+zfPV6WgMfrV5f9P0/XV7U\n3ZmVhHsKZmaWciiYmVnKoWBmZimHgpmZpXyg2cyKLouTBMAnCjQG9xTMzCzlUDAzs5RDwczMUg4F\nMzNLORTMzCzlUDAzs5RDwczMUr5Owcyaja/b7bvddys+h4KZNRsbe3271CW0eA4F26v4L02z+jkU\nbK/ivzTN6ucDzWZmlnIomJlZyqFgZmYph4KZmaUcCmZmlnIomJlZyqFgZmYph4KZmaUcCmZmlnIo\nmJlZyqFgZmYph4KZmaUyDQVJgyW9K2mppOvqeHwfSY8lj8+WVJFlPWZmVr/MQkFSa+Au4BzgGOBi\nScfUavYj4C8RcTjwb8C/ZlWPmZk1LMuewsnA0ohYFhGbgUeBobXaDAUeSpZ/B5wpSRnWZGZm9cgy\nFLoBH+etVyXb6mwTETXAOqBThjWZmVk9srzJTl1/8cdutEHScGB4srpB0rt7WFuTdSh0BlaXuo5d\n8gt37sCfXXO3F3x+hxbSKMtQqAJ65K13B1bupE2VpDbAAcDntXcUEZOASRnV2aRImhsR/Utdh+06\nf3bNmz+/nCyHj+YAvST1lNQOGAZMq9VmGnB5snwB8F8RsUNPwczMGkdmPYWIqJE0AngBaA08EBFL\nJI0D5kbENOA3wFRJS8n1EIZlVY+ZmTVM/sO8aZE0PBkus2bGn13z5s8vx6FgZmYpT3NhZmYph0Ij\nkbRV0vy8rwpJ/SVN3IV9dJR0VZZ17s0kjZW0RNLC5DM6pZFff4Ck5xrzNVsqSZ3yftaqJa1IltdK\nensnzxkn6awC9l0haXHxq24asjwl1bb3ZUQcX2vbcmBu7YaS2iQX89XWEbgKuLv45e3dJJ0KfAc4\nMSK+ktQZaFfismw3RcQa4HgASTcDGyJiQjK/Wp3BGxE31bVdUuuI2JpNpU2PewollP+XoaSbJU2S\n9CIwRVJvSW8mf90slNQL+BVwWLLt9pIW3/IcBKyOiK8AImJ1RKyU1E/SK5LmSXpB0kEAkg6X9JKk\nBZL+W9Jhyrld0mJJiyR9L2k7QNJMSb+T9CdJD2+bziWZNPJPkv4InF+qN7+XaS3p/qRX+KKk9gCS\nJku6IFleLumm5HO5MPl/sEDS68DVpSw+aw6FxtM+rzv79E7a9AOGRsT3gSuBXye9i/7kLvS7Dng/\nIo6PiDGNU/Ze40Wgh6Q/S7pb0umS2gJ3AhdERD/gAeC2pP3DwF0R0Rf4H8An5H6pHw/0Bc4Cbt8W\nIsAJwChyk0P+PfAtSWXA/cB5wP8EujbC+zToRe6z6w2sBb67k3abIuK0iHgUeBAYGRGnNlaRpeLh\no8ZT1/BRbdMi4stk+XVgrKTuwFMR8Z7nCsxORGyQ1I/cL+czgMeAW4Fjgf+b/Nu3Bj6RVA50i4in\nk+duApB0GvDbZKjhU0mvACcBXwBvRkRV0m4+UAFsAD6IiPeS7f/J36Zzsex8EBHzk+V55D6LujwG\nIOkAoGNEvJJsn0pu9ucWyaHQtGzcthARj0iaDZwLvCDpn4BlJatsL5D8Mp8JzJS0iNwwwZLafx1K\n2n8nu6gvtb/KW97K3372fE5446v9WbTfSbttP49iL/qcPHzUREn6e2BZREwkNx3IccB6oLykhbVQ\nko5MjttsczzwDtAlOQiNpLaSekfEF+Tm6/rfyfZ9JHUAZgHfk9RaUhfgfwFv1vOyfwJ6SjosWb+4\nyG/LiiAi1gLrkp4gwCWlrCdrDoWm63vA4mSo4ShgSnJGxavJgUwfaC6u/YCHJL0taSG5sf+byM3J\n9a+SFgDzyR0/APgBMDJp+xq54wFPAwuBBcB/AZURUb2zF0yGnYYDv08OaH6YyTuzYrgCuCs50Pxl\nQ42bM1/RbGZmKfcUzMws5VAwM7OUQ8HMzFIOBTMzSzkUzMws5VAw2wXJHFWjS12HWVYcCmZmlnIo\nmNVD0mXJLLULJE2t9diPJc1JHnsyuaoZSRcmFxgukDQr2VbXrLdmTY4vXjPbCUm9gaeAb0XEakkH\nAiP529z8nZKrzJF0K/BpRNyZzJs0OCJWSOoYEWsl3Qm8EREPS2oHtM6b/NCsyXBPwWznBgK/i4jV\nABHxea3Hj5X0/5IQuATonWx/FZgs6cfkZlaF3Ky3P5d0LXCoA8GaKoeC2c41NDvmZGBERPQB/gUo\nA4iIK4EbgB7A/KRH8QgwhNy8OS9IGphl4Wa7y6FgtnMvAxdJ6gSQDB/lKyd3f4W25M2cKemwiJid\n3N5xNbmb99Q1661Zk+P7KZjtREQskXQb8IqkrcBb5O6rvc2NwGxys5su4m/Tmt+eHEgWuWBZQO6u\neZdK2gJUA+Ma5U2Y7SIfaDYzs5SHj8zMLOVQMDOzlEPBzMxSDgUzM0s5FMzMLOVQMDOzlEPBzMxS\nDgUzM0v9f9MEmR1uusXRAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcac99b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='class',y='survived',hue='sex',data=titanic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#0099ff size=5 face=\"黑体\"> 03 计数图</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xe89ca90>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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4Y+g8Y1r4/lnw11V1wWBpVm5x/m9W1aC7Vlbg0cBu93um5SI4E3hH9/78bnq3+x+0A/9d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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd746550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='deck',data=titanic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由此可见，我们选定某个字段，countplot() 会自动帮我们统计该字段下各类别的数目。当然，我们也可以再传入'hue'参数，进行细分，这里我们加入'sex'分类。\n",
    "如果我们希望调换横纵坐标，也就是类别放于纵坐标，计数值横坐标显示，将x轴换为y轴即可。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xe9582e8>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0xfa10080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(y='deck',hue='who',data=titanic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#0099ff size=5 face=\"黑体\"> 04 散点图</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xc6698d0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0xc669748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#在seaborn中有两种不同的分类散点图。stripplot() 使用的方法是用少量的随机“抖动”调整分类轴上的点的位置，\n",
    "#swarmplot() 表示的是带分布属性的散点图。\n",
    "sns.stripplot(x='embarked',y='fare',data=titanic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x5b561d0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HQBvn3A/N7GLg28DFwDDgd865YXV9RlMdSb0wbxfLN+/l9OPa06V13Y847ios5r3lW+mY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\nSCAFhIiIBFJAiIhIIAWEiIgE+n9ISbIhFTd1pwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcadc1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#这里我们可以通过设置'jitter'参数控制抖动的大小。\n",
    "sns.stripplot(x='embarked',y='fare',\n",
    "                    data=titanic,jitter=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xcadc908>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tLsNJbSqkC1z+gmPZHQt1BtfyfL0vdafhutsqvLce7+g0UqfgAOh7g/4R4jxy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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xce58da0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#swarmplot() 方法使用防止它们重叠的算法沿着分类轴调整点。它可以更好地表示观测的分布，它适用于相对较小的数据集。\n",
    "sns.swarmplot(x='embarked',y='fare',data=titanic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xced48d0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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kuEaF1Nu/l8CN720mIfk8QT8/xF63+/nN7QH+pF0J0CTynbRoWoPDokXrxozF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\nddz/A659hkklkZmCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcad2080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#可以通过'hue'参数，对散点图添加更多细分的维度，Seaborn 中会以颜色来进行区分。\n",
    "sns.stripplot(x='embarked',y='age',hue='who',jitter=1,data=titanic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#0099ff size=5 face=\"黑体\"> 05 箱线图</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xcea5470>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0xcf3b240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#boxplot（箱线图）是一种用作显示一组数据分散情况的统计图。它能显示出一组数据的最大值、最小值、中位数及上下四分位数。因形状如箱子而得名。\n",
    "#这意味着箱线图中的每个值对应于数据中的实际观察值。\n",
    "sns.boxplot(x='class',y='age',data=titanic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xcfbfbe0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Rbupt1+d0eiAiEnNKBCIiMadEICISc0oEIiIxp0QgIhJzGjUkEoFIxqGDakVJ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\nIhJzSgQiIjGnRCAiEnNKBCIiMff/AdfT8lQK+LwuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcad2d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#同样的，可以通过传入'hue'的参数，来对x轴的字段进行细分，这里我们通过'who'来进行分类观察。\n",
    "sns.boxplot(x='class',y='age',hue='who',data=titanic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xd1247f0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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BHsPi2hP80nVzkCRaa+irROtNFwKrgLOBV4hWmTPGl373u99xzz33ABwLfA+L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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd0d0ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#调节'order' 和 'hue_order' 参数，我们可以控制x轴展示的顺序。\n",
    "fig,axes=plt.subplots(1,2) \n",
    "\n",
    "sns.boxplot(x='class',y='age',hue='who',\n",
    "                    data=titanic,ax=axes[0])\n",
    "\n",
    "sns.boxplot(x='class',y='age',hue='who',data=titanic,\n",
    "                    order=['Third','Second','First'],\n",
    "                    hue_order=['child','woman','man'],ax=axes[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xd0d08d0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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9TwvH6AVcBfwi8+HFm5mNBM4HTnH3f5pZMdAt4rAkTe7eAAwDMLNbgJ3uPtPM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\nCEREYk6JQEQk5pQIRERi7v8DLd5EN3A8W9IAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd0c37f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#可以通过'linewidth'参数，控制线条的粗细。我们把'linewidth'参数设为1，就可以看到整体图形的线条变细，你可以根据自己的需要调节。\n",
    "sns.boxplot(x='class',y='age',hue='who',\n",
    "                    linewidth=1,data=titanic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#0099ff size=5 face=\"黑体\"> 06 小提琴图</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "小提琴图其实是箱线图与核密度图的结合，箱线图展示了分位数的位置，小提琴图则展示了任意位置的密度，通过小提琴图可以知道哪些位置的密度较高。 \n",
    "\n",
    "在图中，白点是中位数，黑色盒型的范围是下四分位点到上四分位点，细黑线表示须。外部形状即为核密度估计。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xd3d31d0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Jk/joo7C6rBYy+/bt48mnnoQMUAPCaB8HJ/hG+CguLubxKY9H5DIujQ0Cj1LK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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd3da2b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x='class',y='age',data=titanic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xd3f8dd8>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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NMIA0vXk0NLonBD09PViWNaqep9Bjpe0uPJ1JaOtSStkCXOfyuUwawghz6eWX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\nOAeBmVnG/ReWMr5PpXMqAwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcfd6ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#同样，可以设置'hue'参数，对字段进行细分。\n",
    "sns.violinplot(x='class',y='age',hue='who',data=titanic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#0099ff size=5 face=\"黑体\"> 07 回归图</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xc6cc160>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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k9FSMt65C7qOcOrQBinLakq9pSCFNRZb/4y+zVTvGDCdeqyq87P7H3yvoGus2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\n0RAp+BERDZGCHxHRECn4ERENcRW6KBtt8/rt0AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc694dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "iris=sns.load_dataset('iris')\n",
    "sns.regplot(x='sepal_length',y='petal_length',data=iris)\n",
    "#首先来看 'sepal_length' 和 'petal_length' 之间的线性关系。\n",
    "#图中的点表示实际的数据点，Seaborn 根据这些数据拟合出直线，表示x轴和y轴对应字段之间的线性关系，直线周围的阴影表示置信区间。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x6d444e0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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z+Y0xPPf+Pi75ycsseWkb7f4gw4pzefC6M/nzvPOZUFoYs0Z8rPORiDrz6ZAi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\nL8WzIgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc6f1780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#关于置信区间，可以通过设置'ci'参数控制是否显示。\n",
    "sns.regplot(x='sepal_length',y='petal_length',data=iris,ci=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xceb6358>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ko9d207Hv2D4GPDeAjLQMesX2qtKoBKizaUl1Kj970b8u4uecnzk57mR+yPqB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\nY5BgCt8wDGOQ8P8xURUOcZdxZQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x3a46d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#可以通过'color'和'marker'参数来控制图形的颜色以及数据点的形状。\n",
    "fig,axes=plt.subplots(1,2) \n",
    "\n",
    "sns.regplot(x='sepal_length',y='petal_length',data=iris,\n",
    "            color='r',marker='+',ax=axes[0])\n",
    "\n",
    "sns.regplot(x='sepal_length',y='petal_length',data=iris,\n",
    "            color='g',marker='*',ax=axes[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0xcc118d0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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bz7md2aNnJ5w36t6A956Atno+do/CUzqKN1s+xkTVxvJsedww+QZunXorY/LH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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcc11438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#lmplot() 可以设置hue，进行多个类别的显示，而 regplot() 是不支持的。\n",
    "#这里我们通过设置hue='species'，来进行分类别地展示。\n",
    "sns.lmplot(x='sepal_length',y='petal_length',\n",
    "                 hue='species',data=iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0xd0e6b70>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Bi8sCl1dIxZs9zdhxdgc2VGxo5YF4VfpV0Cq1GJo8FIvyF7W7rlapFaa96pSQAyv7DD1R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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd0c5748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#同样的，我们也可以更改数据点的形状，来进行区分。\n",
    "sns.lmplot(x='sepal_length',y='petal_length',hue='species',\n",
    "                    data=iris,markers=['*','o','+'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0xd2b4a58>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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BwQqmyny08pcM4uTPRWSlwyUpSMmqa7QtMdWDwyWmahaOHDmyav/+/Ynbt29P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\nDwSIFK3uzkC5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd466550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#设置'fit_reg'参数，可以控制是否显示拟合的直线。\n",
    "sns.lmplot(x='sepal_length',y='petal_length',hue='species',\n",
    "                data=iris,markers=['*','o','+'],fit_reg=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0xd4d2390>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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9rlBq3O9S8eD6Ouze3IBli8e/bq5YwCAiIiIiIiKaJ57Y3oSnDrYhkjDh1Z3ATsOSeGJ7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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd2b4d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#如果要对不同的类别分开绘制，用'col'参数代替'hue'。\n",
    "sns.lmplot(x='sepal_length',y='petal_length',\n",
    "                col='species',data=iris)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#0099ff size=5 face=\"黑体\"> 08 热力图</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xd85ef28>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ROufBiu18XMW2tPMae0paSKq1fKmk3wInRMTZFcIORMS9Jf6+JfUD2+btLuAP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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd86a160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "flights = sns.load_dataset(\"flights\")\n",
    "flights.head(10)\n",
    "f=flights.pivot('year','month','passengers')\n",
    "sns.heatmap(f)\n",
    "#我们以'year'为纵轴，'month'为横轴，'passengers'的值为标准绘制热力图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xc79a860>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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gUzj6IqdskJGRkflefpDdOvoiB34ZGRmZ7+Unm+OXA7+MjIzM9yJP9fwYOFpa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yfQGBPq8Xk1l3Tg+jSn7MiiID2bA4vWEj+oM1GtGjJ4yeMM+flJQiLDGLzkMQBydx0gookJlUiI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\ndQy747exsbGpY/w/weVu4ObdS5kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd834438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#如果要显示具体的数值，可以通过'annot'参数来控制。\n",
    "sns.heatmap(f, annot=True,fmt=\"d\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xdcf5630>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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RX+bqiYiQ9AfgD8BqYDPgFElnRcR7J372pLH/QdImwKHAcZKCVHDmxIhYVrHp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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xdcf5a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#通过 Seaborn 的调色板控制热力图显示的颜色，调色板在后续会有详细的说明，这里只做演示，示例热力图的颜色调节机制。\n",
    "cmap = sns.diverging_palette(200,20,sep=20,as_cmap=True)\n",
    "sns.heatmap(f,cmap=cmap)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#0099ff size=5 face=\"黑体\"> 09 图形控制的艺术</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xc860a90>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AWrJmsEfEzZ1oBACQBssdASAzRZc7/pXtuqQ/k/RD2w+maQsAsF5FV8XcK+neRL0AABJg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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xdcf7278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#创建一个20行6列的数据\n",
    "import numpy as np\n",
    "data = np.random.normal(size=(20, 6)) + np.arange(6) / 2\n",
    "sns.boxplot(data=data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Seaborn 中有 white / whitegrid / dark / darkgrid / ticks 几种样式，用 set_style() 函数控制，分别如下：\n",
    "whitegrid 白色网格背景\n",
    "white 白色背景（默认）\n",
    "darkgrid 黑色网格背景\n",
    "dark 黑色背景\n",
    "ticks 四周带有刻度的白色背景"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xe796d68>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PqluEBRnjBW6purpa7e3tSiaTbP6UJa4Du6CgQD/72c9M1gLAIvX19ero6JDE5k/ZwtJ0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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xe79ae48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设为白色网格背景\n",
    "sns.set_style(\"whitegrid\")\n",
    "sns.boxplot(data=data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xe85e588>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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UV1en4eFhtbS03PI5sVi5Tp53rbpFWIwxXuC65syJa9++d0eHQtn8yX+eAzscDmvjxo0m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\nWILABgBLENgAYAkCGwAsQWADgCX+D8uQCKrqryIIAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xdd5d550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设为黑色网格背景\n",
    "sns.set_style(\"darkgrid\")\n",
    "sns.boxplot(data=data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "seaborn 中的分类色板，主要用 color_palette() 函数控制，color_palette() 不写参数则显示为 Seaborn 默认颜色。如果需要设置所有图形的颜色，则用 set_palette() 函数定义。\n",
    "Seaborn 中6个默认的颜色循环主题分别为： deep, muted, pastel, bright, dark, colorblind，下面我们列举演示。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xe97f5f8>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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pVPbvRSqV1uuv76LLNqCqavq4j7lumxYsWKDu7m5J0qFDh3TXXXe5HQqAhTj8Kf9cd9j3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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xe869668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设置颜色模式为'deep'\n",
    "sns.boxplot(data=data,palette=sns.color_palette('deep'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xe8365c0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0xea4b5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#需要注意的是，除了默认的颜色模式有10中颜色外，其他的颜色模式只有6种颜色，如果需要更多颜色，那么则需要采用hls色彩空间。\n",
    "#创建一个20行10列的数据'data2'\n",
    "data2 = np.random.normal(size=(20, 10)) + np.arange(10) / 2  \n",
    "\n",
    "#利用hls色彩空间进行调色\n",
    "sns.boxplot(data=data2, palette=sns.color_palette('hls', 10))  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xef5f5f8>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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DystHP07O8Rj2ggUL9MEHH0iSjh8/rnnz5jltCoCF2Pwp8xz3sKuqqvThhx+qtrZWqVRK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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xef88b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#可以尝试 Reds/Greens，默认颜色由浅到深\n",
    "sns.boxplot(data=data,palette=sns.color_palette('Blues'))  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'mpl' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-21-cc0634c37dae>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m#Seaborn 对中文的显示不太友好，如果在遇到乱码问题时，可以加入下面的代码。\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;31m# 指定默认字体\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mmpl\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrcParams\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'font.sans-serif'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;34m'SimHei'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;31m# 解决保存图像是负号'-'显示为方块的问题\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'mpl' is not defined"
     ]
    }
   ],
   "source": [
    "#Seaborn 对中文的显示不太友好，如果在遇到乱码问题时，可以加入下面的代码。\n",
    "# 指定默认字体\n",
    "mpl.rcParams['font.sans-serif'] = ['SimHei']  \n",
    "\n",
    "# 解决保存图像是负号'-'显示为方块的问题 \n",
    "mpl.rcParams['axes.unicode_minus'] = False  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x101fd390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#画出的图形我们需要保存，可以先建立一个画布，设置我们图像的大小，然后将这个画布保存下来。\n",
    "#设置一个（12，6）的画布\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "#图形绘制代码\n",
    "sns.boxplot(data=data,palette=sns.color_palette('Blues')) \n",
    "\n",
    "#将画布保存为'xiang.png'，还可以保存为jpg、svg格式图片\n",
    "plt.savefig('xiang.png')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
